Adversarial Machine Learning: The Case of Recommendation Systems

Anh Truong, Negar Kiyavash, Seyed Rasoul Etesami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Learning with expert advice framework has drawn much attention in recent years especially in the context of recommendation systems. We consider two challenges that we face in broadly applying this framework in practice. One is the impact of adversarial attack strategies (malicious recommendations) and the other is lack of sufficient recommendation from quality experts (aka sleeping expert setting). In this paper, we discuss some recent results on understanding adversarial strategies and their effect on recommendation systems. In addition, in the sleeping expert setting, we discuss some novel designs for learning alaorithms and the analysis of their convergence properties.

Original languageEnglish (US)
Title of host publication2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538635124
DOIs
StatePublished - Aug 24 2018
Event19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 - Kalamata, Greece
Duration: Jun 25 2018Jun 28 2018

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2018-June

Conference

Conference19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
CountryGreece
CityKalamata
Period6/25/186/28/18

Keywords

  • Learning with expert advice
  • adversarial strategy
  • sleeping experts

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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  • Cite this

    Truong, A., Kiyavash, N., & Rasoul Etesami, S. (2018). Adversarial Machine Learning: The Case of Recommendation Systems. In 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 [8445767] (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2018.8445767